Summary"Quantum information was born from the merging of classical information and quantum physics. Its main objective consists of understanding the quantum nature of information and learning how to process it by using physical systems which operate by following quantum mechanics laws. Quantum simulation is a fundamental instrument to investigate phenomena of quantum systems dynamics, such as quantum transport, particle localizations and energy transfer, quantum-to-classical transition, and even quantum improved computation, all tasks that are hard to simulate with classical approaches. Within this framework integrated photonic circuits have a strong potential to realize quantum information processing by optical systems.
The aim of 3D-QUEST is to develop and implement quantum simulation by exploiting 3-dimensional integrated photonic circuits. 3D-QUEST is structured to demonstrate the potential of linear optics to implement a computational power beyond the one of a classical computer. Such ""hard-to-simulate"" scenario is disclosed when multiphoton-multimode platforms are realized. The 3D-QUEST research program will focus on three tasks of growing difficulty.
A-1. To simulate bosonic-fermionic dynamics with integrated optical systems acting on 2 photon entangled states.
A-2. To pave the way towards hard-to-simulate, scalable quantum linear optical circuits by investigating m-port interferometers acting on n-photon states with n>2.
A-3. To exploit 3-dimensional integrated structures for the observation of new quantum optical phenomena and for the quantum simulation of more complex scenarios.
3D-QUEST will exploit the potential of the femtosecond laser writing integrated waveguides. This technique will be adopted to realize 3-dimensional capabilities and high flexibility, bringing in this way the optical quantum simulation in to new regime."

"Quantum information was born from the merging of classical information and quantum physics. Its main objective consists of understanding the quantum nature of information and learning how to process it by using physical systems which operate by following quantum mechanics laws. Quantum simulation is a fundamental instrument to investigate phenomena of quantum systems dynamics, such as quantum transport, particle localizations and energy transfer, quantum-to-classical transition, and even quantum improved computation, all tasks that are hard to simulate with classical approaches. Within this framework integrated photonic circuits have a strong potential to realize quantum information processing by optical systems.
The aim of 3D-QUEST is to develop and implement quantum simulation by exploiting 3-dimensional integrated photonic circuits. 3D-QUEST is structured to demonstrate the potential of linear optics to implement a computational power beyond the one of a classical computer. Such ""hard-to-simulate"" scenario is disclosed when multiphoton-multimode platforms are realized. The 3D-QUEST research program will focus on three tasks of growing difficulty.
A-1. To simulate bosonic-fermionic dynamics with integrated optical systems acting on 2 photon entangled states.
A-2. To pave the way towards hard-to-simulate, scalable quantum linear optical circuits by investigating m-port interferometers acting on n-photon states with n>2.
A-3. To exploit 3-dimensional integrated structures for the observation of new quantum optical phenomena and for the quantum simulation of more complex scenarios.
3D-QUEST will exploit the potential of the femtosecond laser writing integrated waveguides. This technique will be adopted to realize 3-dimensional capabilities and high flexibility, bringing in this way the optical quantum simulation in to new regime."

Max ERC Funding

1 474 800 €

Duration

Start date: 2012-08-01, End date: 2017-07-31

Project acronym3DSPIN

Project3-Dimensional Maps of the Spinning Nucleon

Researcher (PI)Alessandro Bacchetta

Host Institution (HI)UNIVERSITA DEGLI STUDI DI PAVIA

Call DetailsConsolidator Grant (CoG), PE2, ERC-2014-CoG

SummaryHow does the inside of the proton look like? What generates its spin? 3DSPIN will deliver essential information to answer these questions at the frontier of subnuclear physics.
At present, we have detailed maps of the distribution of quarks and gluons in the nucleon in 1D (as a function of their momentum in a single direction). We also know that quark spins account for only about 1/3 of the spin of the nucleon.
3DSPIN will lead the way into a new stage of nucleon mapping, explore the distribution of quarks in full 3D momentum space and obtain unprecedented information on orbital angular momentum.
Goals
1. extract from experimental data the 3D distribution of quarks (in momentum space), as described by Transverse-Momentum Distributions (TMDs);
2. obtain from TMDs information on quark Orbital Angular Momentum (OAM).
Methodology
3DSPIN will implement state-of-the-art fitting procedures to analyze relevant experimental data and extract quark TMDs, similarly to global fits of standard parton distribution functions. Information about quark angular momentum will be obtained through assumptions based on theoretical considerations. The next five years represent an ideal time window to accomplish our goals, thanks to the wealth of expected data from deep-inelastic scattering experiments (COMPASS, Jefferson Lab), hadronic colliders (Fermilab, BNL, LHC), and electron-positron colliders (BELLE, BABAR). The PI has a strong reputation in this field. The group will operate in partnership with the Italian National Institute of Nuclear Physics and in close interaction with leading experts and experimental collaborations worldwide.
Impact
Mapping the 3D structure of chemical compounds has revolutionized chemistry. Similarly, mapping the 3D structure of the nucleon will have a deep impact on our understanding of the fundamental constituents of matter. We will open new perspectives on the dynamics of quarks and gluons and sharpen our view of high-energy processes involving nucleons.

How does the inside of the proton look like? What generates its spin? 3DSPIN will deliver essential information to answer these questions at the frontier of subnuclear physics.
At present, we have detailed maps of the distribution of quarks and gluons in the nucleon in 1D (as a function of their momentum in a single direction). We also know that quark spins account for only about 1/3 of the spin of the nucleon.
3DSPIN will lead the way into a new stage of nucleon mapping, explore the distribution of quarks in full 3D momentum space and obtain unprecedented information on orbital angular momentum.
Goals
1. extract from experimental data the 3D distribution of quarks (in momentum space), as described by Transverse-Momentum Distributions (TMDs);
2. obtain from TMDs information on quark Orbital Angular Momentum (OAM).
Methodology
3DSPIN will implement state-of-the-art fitting procedures to analyze relevant experimental data and extract quark TMDs, similarly to global fits of standard parton distribution functions. Information about quark angular momentum will be obtained through assumptions based on theoretical considerations. The next five years represent an ideal time window to accomplish our goals, thanks to the wealth of expected data from deep-inelastic scattering experiments (COMPASS, Jefferson Lab), hadronic colliders (Fermilab, BNL, LHC), and electron-positron colliders (BELLE, BABAR). The PI has a strong reputation in this field. The group will operate in partnership with the Italian National Institute of Nuclear Physics and in close interaction with leading experts and experimental collaborations worldwide.
Impact
Mapping the 3D structure of chemical compounds has revolutionized chemistry. Similarly, mapping the 3D structure of the nucleon will have a deep impact on our understanding of the fundamental constituents of matter. We will open new perspectives on the dynamics of quarks and gluons and sharpen our view of high-energy processes involving nucleons.

Summary"Understanding the dawn of the first galaxies and how their light permeated the early Universe is at the very frontier of modern astrophysical cosmology. Generous resources, including ambitions observational programs, are being devoted to studying these epochs of Cosmic Dawn (CD) and Reionization (EoR). In order to interpret these observations, we propose to build on our widely-used, semi-numeric simulation tool, 21cmFAST, and apply it to observations. Using sub-grid, semi-analytic models, we will incorporate additional physical processes governing the evolution of sources and sinks of ionizing photons. The resulting state-of-the-art simulations will be well poised to interpret topical observations of quasar spectra and the cosmic 21cm signal. They would be both physically-motivated and fast, allowing us to rapidly explore astrophysical parameter space. We will statistically quantify the resulting degeneracies and constraints, providing a robust answer to the question, ""What can we learn from EoR/CD observations?"" As an end goal, these investigations will help us understand when the first generations of galaxies formed, how they drove the EoR, and what are the associated large-scale observational signatures."

"Understanding the dawn of the first galaxies and how their light permeated the early Universe is at the very frontier of modern astrophysical cosmology. Generous resources, including ambitions observational programs, are being devoted to studying these epochs of Cosmic Dawn (CD) and Reionization (EoR). In order to interpret these observations, we propose to build on our widely-used, semi-numeric simulation tool, 21cmFAST, and apply it to observations. Using sub-grid, semi-analytic models, we will incorporate additional physical processes governing the evolution of sources and sinks of ionizing photons. The resulting state-of-the-art simulations will be well poised to interpret topical observations of quasar spectra and the cosmic 21cm signal. They would be both physically-motivated and fast, allowing us to rapidly explore astrophysical parameter space. We will statistically quantify the resulting degeneracies and constraints, providing a robust answer to the question, ""What can we learn from EoR/CD observations?"" As an end goal, these investigations will help us understand when the first generations of galaxies formed, how they drove the EoR, and what are the associated large-scale observational signatures."

Max ERC Funding

1 468 750 €

Duration

Start date: 2015-05-01, End date: 2021-01-31

Project acronymAMDROMA

ProjectAlgorithmic and Mechanism Design Research in Online MArkets

Researcher (PI)Stefano LEONARDI

Host Institution (HI)UNIVERSITA DEGLI STUDI DI ROMA LA SAPIENZA

Call DetailsAdvanced Grant (AdG), PE6, ERC-2017-ADG

SummaryOnline markets currently form an important share of the global economy. The Internet hosts classical markets (real-estate, stocks, e-commerce) as well allowing new markets with previously unknown features (web-based advertisement, viral marketing, digital goods, crowdsourcing, sharing economy). Algorithms play a central role in many decision processes involved in online markets. For example, algorithms run electronic auctions, trade stocks, adjusts prices dynamically, and harvest big data to provide economic information. Thus, it is of paramount importance to understand the algorithmic and mechanism design foundations of online markets.
The algorithmic research issues that we consider involve algorithmic mechanism design, online and approximation algorithms, modelling uncertainty in online market design, and large-scale data analysisonline and approximation algorithms, large-scale optimization and data mining. The aim of this research project is to combine these fields to consider research questions that are central for today's Internet economy. We plan to apply these techniques so as to solve fundamental algorithmic problems motivated by web-basedInternet advertisement, Internet market designsharing economy, and crowdsourcingonline labour marketplaces. While my planned research is focussedcentered on foundational work with rigorous design and analysis of in algorithms and mechanismsic design and analysis, it will also include as an important component empirical validation on large-scale real-life datasets.

Online markets currently form an important share of the global economy. The Internet hosts classical markets (real-estate, stocks, e-commerce) as well allowing new markets with previously unknown features (web-based advertisement, viral marketing, digital goods, crowdsourcing, sharing economy). Algorithms play a central role in many decision processes involved in online markets. For example, algorithms run electronic auctions, trade stocks, adjusts prices dynamically, and harvest big data to provide economic information. Thus, it is of paramount importance to understand the algorithmic and mechanism design foundations of online markets.
The algorithmic research issues that we consider involve algorithmic mechanism design, online and approximation algorithms, modelling uncertainty in online market design, and large-scale data analysisonline and approximation algorithms, large-scale optimization and data mining. The aim of this research project is to combine these fields to consider research questions that are central for today's Internet economy. We plan to apply these techniques so as to solve fundamental algorithmic problems motivated by web-basedInternet advertisement, Internet market designsharing economy, and crowdsourcingonline labour marketplaces. While my planned research is focussedcentered on foundational work with rigorous design and analysis of in algorithms and mechanismsic design and analysis, it will also include as an important component empirical validation on large-scale real-life datasets.

Max ERC Funding

1 780 150 €

Duration

Start date: 2018-07-01, End date: 2023-06-30

Project acronymBACKUP

ProjectUnveiling the relationship between brain connectivity and function by integrated photonics

Researcher (PI)Lorenzo PAVESI

Host Institution (HI)UNIVERSITA DEGLI STUDI DI TRENTO

Call DetailsAdvanced Grant (AdG), PE7, ERC-2017-ADG

SummaryI will address the fundamental question of which is the role of neuron activity and plasticity in information elaboration and storage in the brain. I, together with an interdisciplinary team, will develop a hybrid neuro-morphic computing platform. Integrated photonic circuits will be interfaced to both electronic circuits and neuronal circuits (in vitro experiments) to emulate brain functions and develop schemes able to supplement (backup) neuronal functions. The photonic network is based on massive reconfigurable matrices of nonlinear nodes formed by microring resonators, which enter in regime of self-pulsing and chaos by positive optical feedback. These networks resemble human brain. I will push this analogy further by interfacing the photonic network with neurons making hybrid network. By using optogenetics, I will control the synaptic strengthen-ing and the neuron activity. Deep learning algorithms will model the biological network functionality, initial-ly within a separate artificial network and, then, in an integrated hybrid artificial-biological network.
My project aims at:
1. Developing a photonic integrated reservoir-computing network (RCN);
2. Developing dynamic memories in photonic integrated circuits using RCN;
3. Developing hybrid interfaces between a neuronal network and a photonic integrated circuit;
4. Developing a hybrid electronic, photonic and biological network that computes jointly;
5. Addressing neuronal network activity by photonic RCN to simulate in vitro memory storage and retrieval;
6. Elaborating the signal from RCN and neuronal circuits in order to cope with plastic changes in pathologi-cal brain conditions such as amnesia and epilepsy.
The long-term vision is that hybrid neuromorphic photonic networks will (a) clarify the way brain thinks, (b) compute beyond von Neumann, and (c) control and supplement specific neuronal functions.

I will address the fundamental question of which is the role of neuron activity and plasticity in information elaboration and storage in the brain. I, together with an interdisciplinary team, will develop a hybrid neuro-morphic computing platform. Integrated photonic circuits will be interfaced to both electronic circuits and neuronal circuits (in vitro experiments) to emulate brain functions and develop schemes able to supplement (backup) neuronal functions. The photonic network is based on massive reconfigurable matrices of nonlinear nodes formed by microring resonators, which enter in regime of self-pulsing and chaos by positive optical feedback. These networks resemble human brain. I will push this analogy further by interfacing the photonic network with neurons making hybrid network. By using optogenetics, I will control the synaptic strengthen-ing and the neuron activity. Deep learning algorithms will model the biological network functionality, initial-ly within a separate artificial network and, then, in an integrated hybrid artificial-biological network.
My project aims at:
1. Developing a photonic integrated reservoir-computing network (RCN);
2. Developing dynamic memories in photonic integrated circuits using RCN;
3. Developing hybrid interfaces between a neuronal network and a photonic integrated circuit;
4. Developing a hybrid electronic, photonic and biological network that computes jointly;
5. Addressing neuronal network activity by photonic RCN to simulate in vitro memory storage and retrieval;
6. Elaborating the signal from RCN and neuronal circuits in order to cope with plastic changes in pathologi-cal brain conditions such as amnesia and epilepsy.
The long-term vision is that hybrid neuromorphic photonic networks will (a) clarify the way brain thinks, (b) compute beyond von Neumann, and (c) control and supplement specific neuronal functions.

Max ERC Funding

2 499 825 €

Duration

Start date: 2018-11-01, End date: 2023-10-31

Project acronymBIHSNAM

ProjectBio-inspired Hierarchical Super Nanomaterials

Researcher (PI)Nicola Pugno

Host Institution (HI)UNIVERSITA DEGLI STUDI DI TRENTO

Call DetailsStarting Grant (StG), PE8, ERC-2011-StG_20101014

Summary"Nanomaterials such as carbon nanotubes or graphene sheets represent the future of material science, due to their potentially exceptional mechanical properties. One great drawback of all artificial materials, however, is the decrease of strength with increasing toughness, and viceversa. This problem is not encountered in many biological nanomaterials (e.g. spider silk, bone, nacre). Other biological materials display exceptional adhesion or damping properties, and can be self-cleaning or self-healing. The “secret” of biomaterials seems to lie in “hierarchy”: several levels can often be identified (2 in nacre, up to 7 in bone and dentine), from nano- to micro-scale.
The idea of this project is to combine Nature and Nanotechnology to design hierarchical composites with tailor made characteristics, optimized with respect to both strength and toughness, as well as materials with strong adhesion/easy detachment, smart damping, self-healing/-cleaning properties or controlled energy dissipation. For example, one possible objective is to design the “world’s toughest composite material”. The potential impact and importance of these goals on materials science, the high-tech industry and ultimately the quality of human life could be considerable.
In order to tackle such a challenging design process, the PI proposes to adopt ultimate nanomechanics theoretical tools corroborated by continuum or atomistic simulations, multi-scale numerical parametric simulations and Finite Element optimization procedures, starting from characterization experiments on biological- or nano-materials, from the macroscale to the nanoscale. Results from theoretical, numerical and experimental work packages will be applied to a specific case study in an engineering field of particular interest to demonstrate importance and feasibility, e.g. an airplane wing with a considerably enhanced fatigue resistance and reduced ice-layer adhesion, leading to a 10 fold reduction in wasted fuel."

"Nanomaterials such as carbon nanotubes or graphene sheets represent the future of material science, due to their potentially exceptional mechanical properties. One great drawback of all artificial materials, however, is the decrease of strength with increasing toughness, and viceversa. This problem is not encountered in many biological nanomaterials (e.g. spider silk, bone, nacre). Other biological materials display exceptional adhesion or damping properties, and can be self-cleaning or self-healing. The “secret” of biomaterials seems to lie in “hierarchy”: several levels can often be identified (2 in nacre, up to 7 in bone and dentine), from nano- to micro-scale.
The idea of this project is to combine Nature and Nanotechnology to design hierarchical composites with tailor made characteristics, optimized with respect to both strength and toughness, as well as materials with strong adhesion/easy detachment, smart damping, self-healing/-cleaning properties or controlled energy dissipation. For example, one possible objective is to design the “world’s toughest composite material”. The potential impact and importance of these goals on materials science, the high-tech industry and ultimately the quality of human life could be considerable.
In order to tackle such a challenging design process, the PI proposes to adopt ultimate nanomechanics theoretical tools corroborated by continuum or atomistic simulations, multi-scale numerical parametric simulations and Finite Element optimization procedures, starting from characterization experiments on biological- or nano-materials, from the macroscale to the nanoscale. Results from theoretical, numerical and experimental work packages will be applied to a specific case study in an engineering field of particular interest to demonstrate importance and feasibility, e.g. an airplane wing with a considerably enhanced fatigue resistance and reduced ice-layer adhesion, leading to a 10 fold reduction in wasted fuel."

Max ERC Funding

1 004 400 €

Duration

Start date: 2012-01-01, End date: 2016-12-31

Project acronymBioMNP

ProjectUnderstanding the interaction between metal nanoparticles and biological membranes

Researcher (PI)Giulia Rossi

Host Institution (HI)UNIVERSITA DEGLI STUDI DI GENOVA

Call DetailsStarting Grant (StG), PE3, ERC-2015-STG

SummaryThe BioMNP objective is the molecular-level understanding of the interactions between surface functionalized metal nanoparticles and biological membranes, by means of cutting-edge computational techniques and new molecular models.
Metal nanoparticles (NP) play more and more important roles in pharmaceutical and medical technology as diagnostic or therapeutic devices. Metal NPs can nowadays be engineered in a multitude of shapes, sizes and compositions, and they can be decorated with an almost infinite variety of functionalities. Despite such technological advances, there is still poor understanding of the molecular processes that drive the interactions of metal NPs with cells. Cell membranes are the first barrier encountered by NPs entering living organisms. The understanding and control of the interaction of nanoparticles with biological membranes is therefore of paramount importance to understand the molecular basis of the NP biological effects.
BioMNP will go beyond the state of the art by rationalizing the complex interplay of NP size, composition, functionalization and aggregation state during the interaction with model biomembranes. Membranes, in turn, will be modelled at an increasing level of complexity in terms of lipid composition and phase. BioMNP will rely on cutting-edge simulation techniques and facilities, and develop new coarse-grained models grounded on finer-level atomistic simulations, to study the NP-membrane interactions on an extremely large range of length and time scales.
BioMNP will benefit from important and complementary experimental collaborations, will propose interpretations of the available experimental data and make predictions to guide the design of functional, non-toxic metal nanoparticles for biomedical applications. BioMNP aims at answering fundamental questions at the crossroads of physics, biology and chemistry. Its results will have an impact on nanomedicine, toxicology, nanotechnology and material sciences.

The BioMNP objective is the molecular-level understanding of the interactions between surface functionalized metal nanoparticles and biological membranes, by means of cutting-edge computational techniques and new molecular models.
Metal nanoparticles (NP) play more and more important roles in pharmaceutical and medical technology as diagnostic or therapeutic devices. Metal NPs can nowadays be engineered in a multitude of shapes, sizes and compositions, and they can be decorated with an almost infinite variety of functionalities. Despite such technological advances, there is still poor understanding of the molecular processes that drive the interactions of metal NPs with cells. Cell membranes are the first barrier encountered by NPs entering living organisms. The understanding and control of the interaction of nanoparticles with biological membranes is therefore of paramount importance to understand the molecular basis of the NP biological effects.
BioMNP will go beyond the state of the art by rationalizing the complex interplay of NP size, composition, functionalization and aggregation state during the interaction with model biomembranes. Membranes, in turn, will be modelled at an increasing level of complexity in terms of lipid composition and phase. BioMNP will rely on cutting-edge simulation techniques and facilities, and develop new coarse-grained models grounded on finer-level atomistic simulations, to study the NP-membrane interactions on an extremely large range of length and time scales.
BioMNP will benefit from important and complementary experimental collaborations, will propose interpretations of the available experimental data and make predictions to guide the design of functional, non-toxic metal nanoparticles for biomedical applications. BioMNP aims at answering fundamental questions at the crossroads of physics, biology and chemistry. Its results will have an impact on nanomedicine, toxicology, nanotechnology and material sciences.

Max ERC Funding

1 131 250 €

Duration

Start date: 2016-04-01, End date: 2021-03-31

Project acronymBIOSMA

ProjectMathematics for Shape Memory Technologies in Biomechanics

Researcher (PI)Ulisse Stefanelli

Host Institution (HI)CONSIGLIO NAZIONALE DELLE RICERCHE

Call DetailsStarting Grant (StG), PE1, ERC-2007-StG

SummaryShape Memory Alloys (SMAs) are nowadays widely exploited for the realization of innovative devices and have a great impact on the development of a variety of biomedical applications ranging from orthodontic archwires to vascular stents. The design, realization, and optimization of such devices are quite demanding tasks. Mathematics is involved in this process as a major tool in order to let the modeling more accurate, the numerical simulations more reliable, and the design more effective. Many material properties of SMAs such as martensitic reorientation, training, and ferromagnetic behavior, are still to be properly and efficiently addressed. Therefore, new modeling ideas, along with original analytical and numerical techniques, are required. This project is aimed at addressing novel mathematical issues in order to move from experimental materials results toward the solution of real-scale biomechanical Engineering problems. The research focus will be multidisciplinary and include modeling, analytic, numerical, and computational issues. A progress in the macroscopic description of SMAs, the computational simulation of real-scale SMA devices, and the optimization of the production processes will contribute to advance in the direction of innovative applications.

Shape Memory Alloys (SMAs) are nowadays widely exploited for the realization of innovative devices and have a great impact on the development of a variety of biomedical applications ranging from orthodontic archwires to vascular stents. The design, realization, and optimization of such devices are quite demanding tasks. Mathematics is involved in this process as a major tool in order to let the modeling more accurate, the numerical simulations more reliable, and the design more effective. Many material properties of SMAs such as martensitic reorientation, training, and ferromagnetic behavior, are still to be properly and efficiently addressed. Therefore, new modeling ideas, along with original analytical and numerical techniques, are required. This project is aimed at addressing novel mathematical issues in order to move from experimental materials results toward the solution of real-scale biomechanical Engineering problems. The research focus will be multidisciplinary and include modeling, analytic, numerical, and computational issues. A progress in the macroscopic description of SMAs, the computational simulation of real-scale SMA devices, and the optimization of the production processes will contribute to advance in the direction of innovative applications.

SummaryOne out of 5 people in their fifties will experience a bone fracture due to osteoporosis (OP)-induced fragility in their lifetime. The OP socio-economic burden is dramatic and involves tens of millions of people in the EU, with a steadily increasing number due to population ageing. Current treatments entail drug-therapy coupled with a healthy lifestyle but OP fractures need mechanical fixation to rapidly achieve union: the contribution of biomaterial scientists in this field is still far from taking its expected leading role in cutting-edge research. Bone remodelling is a well-coordinated process of bone resorption by osteoclasts followed by the production of new bone by osteoblasts. This process occurs continuously throughout life in a coupling with a positive balance during growth and negative with ageing, which can result in OP. We believe that an architecture driven stimulation of the osteoclast/osteoblast coupling, with an avant-garde focus on osteoclasts activity, is the key to success in treating unbalanced bone remodelling. We aim to manufacture a scaffold that mimics healthy bone features which will establish a new microenvironment favoring a properly stimulated and active population of osteoclasts and osteoblasts, i.e. a well-balanced bone cooperation. After 5 years we will be able to prove the efficacy of this approach. A benchmark will be set up for OP fracture treatment and for the realization of smart bone substitutes that will be able to locally “trick” aged bone cells stimulating them to act as healthy ones. BOOST results will have an unprecedented impact on the scientific research community, opening a new approach to set up smart, biomimetic strategies to treat aged, unbalanced bone tissues and to reduce OP-associated disabilities and financial burdens.

One out of 5 people in their fifties will experience a bone fracture due to osteoporosis (OP)-induced fragility in their lifetime. The OP socio-economic burden is dramatic and involves tens of millions of people in the EU, with a steadily increasing number due to population ageing. Current treatments entail drug-therapy coupled with a healthy lifestyle but OP fractures need mechanical fixation to rapidly achieve union: the contribution of biomaterial scientists in this field is still far from taking its expected leading role in cutting-edge research. Bone remodelling is a well-coordinated process of bone resorption by osteoclasts followed by the production of new bone by osteoblasts. This process occurs continuously throughout life in a coupling with a positive balance during growth and negative with ageing, which can result in OP. We believe that an architecture driven stimulation of the osteoclast/osteoblast coupling, with an avant-garde focus on osteoclasts activity, is the key to success in treating unbalanced bone remodelling. We aim to manufacture a scaffold that mimics healthy bone features which will establish a new microenvironment favoring a properly stimulated and active population of osteoclasts and osteoblasts, i.e. a well-balanced bone cooperation. After 5 years we will be able to prove the efficacy of this approach. A benchmark will be set up for OP fracture treatment and for the realization of smart bone substitutes that will be able to locally “trick” aged bone cells stimulating them to act as healthy ones. BOOST results will have an unprecedented impact on the scientific research community, opening a new approach to set up smart, biomimetic strategies to treat aged, unbalanced bone tissues and to reduce OP-associated disabilities and financial burdens.

Max ERC Funding

1 977 500 €

Duration

Start date: 2016-05-01, End date: 2021-12-31

Project acronymBRIDGE

ProjectBridging the gap between Gas Emissions and geophysical observations at active volcanoes

Researcher (PI)Alessandro Aiuppa

Host Institution (HI)UNIVERSITA DEGLI STUDI DI PALERMO

Call DetailsStarting Grant (StG), PE10, ERC-2012-StG_20111012

SummaryIn spite of their significance in a variety of volcanological aspects, gas observations at volcanoes have lagged behind geophysical studies for a long time. This has primarily reflected the inherent technical limitations met by gas geochemists in capturing volcanic gas properties (chemistry and flux) at high-rate (1 Hz), and using permanent instrumental arrays. The poor temporal resolution of volcanic gas observations has, in addition, precluded the real-time analysis of fast-occurring volcanic processes, as those occurring shortly prior to eruptions, therefore generally limiting the use of gas geochemistry in volcanic hazard assessment. However, the recent progresses made by modern multi-component/high frequency measurement techniques now open the way for decisive step ahead in the current state-of-the-art to be finally attempted.
The BRIDGE research proposal has the ambitious goals to bridge the existing technological gap between geochemical and geophysical observations at volcanoes. This will be achieved by designing, setting up, and deploying in the field, innovative instruments for 1 Hz observations of volcanic SO2 and CO2 fluxes. From this, the co-acquired volcanic gas and geophysical information will be then combined within a single interpretative framework, therefore contributing to fill our current gap of knowledge on fast (timescales of seconds/minutes) degassing processes, and to deeper exploration of the role played by gas exsolution from (and migration through) silicate liquids as effective source mechanism of the physical signals (e.g., LP and VLP seismicity, and tremor) measured at volcanoes. Finally, this combined volcanic gas-geophysical approach will be used to yield improved modelling/understanding of a variety of volcanic features, including modes/rates of gas separation from magmas, mechanisms of gas flow in conduits, and trigger mechanisms of explosive volcanic eruptions.

In spite of their significance in a variety of volcanological aspects, gas observations at volcanoes have lagged behind geophysical studies for a long time. This has primarily reflected the inherent technical limitations met by gas geochemists in capturing volcanic gas properties (chemistry and flux) at high-rate (1 Hz), and using permanent instrumental arrays. The poor temporal resolution of volcanic gas observations has, in addition, precluded the real-time analysis of fast-occurring volcanic processes, as those occurring shortly prior to eruptions, therefore generally limiting the use of gas geochemistry in volcanic hazard assessment. However, the recent progresses made by modern multi-component/high frequency measurement techniques now open the way for decisive step ahead in the current state-of-the-art to be finally attempted.
The BRIDGE research proposal has the ambitious goals to bridge the existing technological gap between geochemical and geophysical observations at volcanoes. This will be achieved by designing, setting up, and deploying in the field, innovative instruments for 1 Hz observations of volcanic SO2 and CO2 fluxes. From this, the co-acquired volcanic gas and geophysical information will be then combined within a single interpretative framework, therefore contributing to fill our current gap of knowledge on fast (timescales of seconds/minutes) degassing processes, and to deeper exploration of the role played by gas exsolution from (and migration through) silicate liquids as effective source mechanism of the physical signals (e.g., LP and VLP seismicity, and tremor) measured at volcanoes. Finally, this combined volcanic gas-geophysical approach will be used to yield improved modelling/understanding of a variety of volcanic features, including modes/rates of gas separation from magmas, mechanisms of gas flow in conduits, and trigger mechanisms of explosive volcanic eruptions.